Find out why backpropagation and gradient descent are key to prediction in machine learning, then get started with training a simple neural network using gradient descent and Java code.

For example, gradient descent is often used in machine learning in ways that don’t require extreme precision. But a machine learning researcher might want to double the precision of an experiment. In ...

A new publication from Opto-Electronic Advances; DOI 10.29026/oea.2024.230182 , discusses efficient stochastic parallel gradient descent training for on-chip optical processors.

But the real-world questions that interest mathematicians and scientists are rarely simple. In 1847, the French mathematician Augustin-Louis Cauchy was working on a suitably complicated example — ...

Amid all the hype and hysteria about ChatGPT, Bard, and other generative large language models (LLMs), it’s worth taking a step back to look at the gamut of AI algorithms and their uses.After ...

Based on the gradient projection (GP) method, the new algorithm incorporates a novel multiple-path gradient approach to generate the descent direction in consideration of many paths existing in every ...